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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Asada, Daiki Nakagawa, Takuya Hoshi, Yoshikatsu Oya, Hidetoshi Nagai, Shunya Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan

ISBN: (纸本)9798350331820

This paper deals with a design problem for a new event-trigger-based variable gain controller which achieves consensus for multi-agent systems (MASs) with the leader-follower structure. The proposed variable gain controller consists of stabilizing state feedback laws, state feedback inputs for consensus, and compensation inputs with adjustable parameters, and is designed by taking relative positions into account explicitly. In this paper, we show that sufficient conditions for the existence of the proposed formation control system are given in terms of Linear Matrix Inequalities (LMIs). © 2023 IEEE.

关键词： Linear matrix inequalities

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of engineering & Technology 2023.

关键词： Machine learning

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PartDensE: Knowledge Graph Embedding with Joint Use of Specific Learning and Relation-aware Functions 6

PartDensE: Knowledge Graph Embedding with Joint Use of Speci...

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6th International Conference on Internet of Things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Dan, Qiuyue Cui, Delong Peng, Zhiping Li, Qirui He, Jieguang Qiu, JinBo Jilin Institute of Chemical Technology School of Information and Control Engineering Jilin China Guangdong University of Petrochemical Technology School of Electronic and Information Engineering Maoming China Jiangmen Polytechnic Jiangmen China Guangdong University of Petrochemical Technology School of Computer Maoming China

ISBN: (纸本)9798350386974

Knowledge Graph Embedding (KGE) is important to the value of the Knowledge Graph (KG) in its application field. Currently, neural network-based models achieve the most advanced performance. However, these models rarely consider the potential information between entities and relations in KGs, and also suffer from the problems of complex structure and high consumption of computing resources. In this paper, we propose the simple and efficient model PartDensE by using dense network, combining specific sharing layer and relational awareness layer. Specifically, our model learns all entities and relationships individually and can mine hidden features to enrich global information. Also, learn all the information based on each relation and be able to accurately establish associations between entities and relations. PartDensE can capture global and local features and displayed and hide information, retaining as much valuable information as possible. We evaluated PartDensE with 4 indicators across on two baseline datasets. Numerous experimental data prove the effectiveness of our model. © 2024 IEEE.

关键词： Knowledge graph

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Monarch Butterfly Optimization Algorithm for Human-Robot Collaboration Multi-Objective Disassembly Line Balancing Problem

Monarch Butterfly Optimization Algorithm for Human-Robot Col...

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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Wang, Haokun Guo, Feng Guo, Xiwang Wang, Jiacun Qin, Shujin Tang, Ying Liaoning Petrochemical University Artificial Intelligence and Software Fushun China Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. NJ United States Shangqiu Normal University Logistics Management Shangqiu China Rowan University Electrical & Computer Engineering GlassboroNJ United States

ISBN: (纸本)9798350376739

Efficient end-of-life products disassembly is crucial in the remanufacturing process. However, hazardous and repetitive disassembly tasks raise labor costs and decrease safety and efficiency. This work proposes an innovative disassembly algorithm that is inspired by monarch butterfly, aiming at improving disassembly efficiency through the utilization of human-robot collaboration in the context of a hybrid disassembly line for repetitive or hazardous tasks. The model in this paper provides the basis of solving the multi-objective problem and the mixed integer programming problem. The purpose is to improve the profit in the human robot cooperation environment, and reduce the standby time of the workstation as much as possible. Comparison of this algorithm with other intelligent optimization algorithms with experiments shows its competitive performance in both profit and idle time. © 2024 IEEE.

关键词： Profitability

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Optimization Scheduling of Multi-Energy Microgrid Based on the QUBO Quantum Computing Model 19th

Optimization Scheduling of Multi-Energy Microgrid Based on t...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

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Domain Adversarial Interaction Network for Cross-Domain Fault Diagnosis 4th

Domain Adversarial Interaction Network for Cross-Domain Fau...

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Lu, Weikai Chen, Jian Zheng, Hao Fan, Haoyi Wei, Eng Yee Cao, Xinrong Zhang, Deyang School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia Henan Provincial Institute of Scientific and Technical Information Zhengzhou450003 China

ISBN: (纸本)9783031200984

Intelligent fault diagnosis has been widely used in the industry and plays a crucial role in the health management of machinery. In recent years, unsupervised domain adaptation (UDA) has been applied to fault diagnosis, showing excellent performance under variable working conditions. However, most existing UDA-based methods do not consider the temporal relations in the fault signal, resulting in sub-optimal performance. In this paper, we proposed a domain adversarial interaction network (DAIN) to solve this problem. By downsampling sub-sequences of fault signals and interacting with their features, DAIN can obtain feature representations containing the temporal relations. In addition, domain adversarial learning and maximum mean discrepancy (MMD) are applied to DAIN to align the domain discrepancy and distribution discrepancy of source and target domains. We conducted extensive experiments on the public Paderborn University (PU) dataset, and the results demonstrate that the proposed method can achieve higher cross-domain fault diagnosis accuracy than the existing methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Failure analysis

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Geo2ComMap: Deep Learning-Based MIMO Throughput Prediction Using Geographic Data

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IEEE Wireless Communications Letters 2025年第6期14卷 1831-1835页

作者： Lin, Fan-Hao Huang, Tzu-Hao Wen, Chao-Kai Duong, Trung Q. Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Institute of Electrical Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Memorial University Faculty of Engineering and Applied Science NL St. John’sA1C 5S7 Canada Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom

Accurate communication performance prediction is crucial for wireless applications such as network deployment and resource management. Unlike conventional systems with a single transceiver antenna, throughput (Tput) estimation in antenna array-based multiple-output multiple-input (MIMO) systems is computationally intensive, i.e., requiring analysis of channel matrices, rank conditions, and spatial channel quality. These calculations impose significant computational and time burdens. This letter introduces Geo2ComMap, a deep learning-based framework that leverages geographic databases to efficiently estimate multiple communication metrics across an entire area in MIMO systems using only sparse measurements. To mitigate extreme prediction errors, we propose a sparse sampling strategy. Extensive evaluations demonstrate that Geo2ComMap accurately predicts full-area communication metrics, achieving a median absolute error of 27.35 Mbps for Tput values ranging from 0 to 1900 Mbps. © 2012 IEEE.

关键词： Antenna arrays

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Velocity Pausing Particle Swarm Optimization based PID controller Design for Isolated AC Microgrid 3

Velocity Pausing Particle Swarm Optimization based PID Contr...

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3rd IEEE International Conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Kumar, Anil Altaf, Aatif Kumar, Mahendra Alhussainy, Abdullah A. Alghamdi, Sultan Alobaidi, Abdulraheem H. Dr. B R Ambedkar National Institute of Technology Jalandhar Instrumentation and Control Engineering Department Punjab Jalandhar144008 India King Abdulaziz University Faculty of Engineering Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia

ISBN: (纸本)9798350304732

The work addresses PID control design based on the velocity-pausing particle swarm optimization (VPPSO) technique. The suggested control design is utilized to develop a load frequency control (LFC) approach for an isolated microgrid (MG) with heat-pumps (HPs) and electric-vehicles (EVs). The efficiency and effectiveness of suggested control design are assessed when there are randomized solar power and load-demand disturbances. Furthermore, the robustness and effectiveness of suggested control schemes are evaluated under uncertainty in system parameters and different EVs & HPs controller's operating time-scheduling situations. The simulation results demonstrated the efficiency and usefulness of the recommended VPPSO-PID control strategy under several practical situations. © 2023 IEEE.

关键词： Electric Vehicles Load frequency control (LFC) Microgrid PID controller Velocity Pausing PSO (VPPSO)

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Virtual Synchronous Generator Droop control for Renewable Energy Sources

Virtual Synchronous Generator Droop Control for Renewable En...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Cakmak, Fevzi Aykat, Sukru Kazanbaş, Mehmet Cemil Akgul, Sabahattin Department of Electricity and Energy Mardin Atuklu University Mardin Turkey Department of Computer Engineering Mardin Atuklu University Mardin Turkey Department of Control and Automation Engineering Yildiz Technical University Istanbul Turkey Department of Handicrafts Mardin Atuklu University Mardin Turkey

ISBN: (纸本)9798331532611

The connection of large-scale RES (renewable energy source) to the grid and the increase in the efficiency of energy production also causes different power quality problems. It has become mandatory for these inverter-based systems to participate in load frequency control. For this purpose, the design and simulation of a virtual synchronous generator (VSG), which enables RES to operate like synchronous generators, has been carried out in Matlab/Simulink environment. It is observed that the VSG keeps the load frequency stable according to different load conditions. ©2024 IEEE.

关键词： Synchronous generators

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A Case of Cups and a Ball: Utilizing Generative Artificial Intelligence for Human-robotic Collaboration in Task Execution

A Case of Cups and a Ball: Utilizing Generative Artificial I...

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2024 International Automatic control Conference, CACS 2024

作者： Khoirurizka, Nurdin Prajogo, Joy Chrissetyo Perkins, Spencer Kuo, Chao-Hsiang Lin, Hsien-I National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu Taiwan

ISBN: (纸本)9798350354904

Within the domain of robotics, effective interaction between a human collaborator and robot is a topic of great importance. With the continued advancements in Generative Artificial Intelligence (GAI), we propose a prototype system that utilizes GAI and seeks to bridge the gap between the human and robot. This prototype utilizes a Large Language Model (LLM) combined with a vision system for detection and tracking, to allow the GAI system to control a robotic arm and manipulate objects within the action space. We model the action space within our experiments on the 3-cup Monte game where the user can prompt the system to manipulate the cups within the action space based on the ball's location. Experimentation is done on prompts of varying lengths of sequences, and we evaluate our system based on its ability to understand the prompt and correctly execute the desired task. With this collaboration of techniques and technologies, we hope to open the possibilities and extend human and robotic collaboration into new areas. The results of our experiments show promising results to this end. © 2024 IEEE.

关键词： Intelligent systems

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